Engage2Excel Blog

In Part 1 of this blog story I urged professional sourcers to adapt their focus as machine learning and artificial intelligence (AI) play in increasing role in the field. In a nutshell, AI can now do many sourcing activities better and faster than humans. However, there are still important things that humans do better than machines. Sourcers who focus on those things will continue to be in demand, while those who don't adapt may be edged out.

Artificial intelligence (AI) and machine learning are changing the sourcing game, and smart sourcers are adapting. In our quest to stay cutting edge, my team implemented a few new practices discussed at SourceCon, and in this two-part blog I want to share some of those methods.You probably know that AI and machine learning are already a part of our lives. That's how companies like Netflix and Amazon learn your preferences so they can make suggestions. If you use Siri, Google Assistant or Alexa, you interact with machine learning regularly.

With the employment market continuing to tighten, many companies are re-examining the differences between active and passive job seekers.

An active job seeker is motivated to find a new job and actively searches for job opportunities. Passive job seekers are individuals who are currently employed and willing to learn about new career opportunities.

Our December 2016 survey of 940 active and 507 passive job seekers revealed some key differences in the perceptions, preferences and behaviors of active versus passive job seekers. These findings are revealed in our most recent infographic, The Key Differences Between Active and Passive Job Seekers.